Storytelling is all the rage in business today. It has been an important tool of communication in Qualitative studies.

However reading the book ‘The art of thinking clearly’ (author: Rolf Dobelli), reminded us about the influence of researcher on the story they tell, on how we do content analysis.

Dobelli talks about the Story Bias i.e. we understand the world better by weaving stories/meaning into what can be unconnected details. However this often distorts reality and gives us a false sense of understanding. Eventually it affects our ability to make decisions.

In research as well, when we build stories to communicate insights, we designate importance to certain details. We focus on certain elements while leaving out others. The data left out might in fact be useful in explaining the cause. Therein lies an inherent bias which affects the basic foundation of the story we build.

A researcher can be more aware of their own in built influences that affect the way they look at data. However we need more specific methods and tools to ensure that the story bias does not seep into the analysis. We have managed to do this by developing specific systems. Here are three of them:

Content analysis by teams rather than individuals for diverse thinking

Serious consideration of ‘wasted data’

Building frameworks to validate how data is structured

And so listeners of business stories need to be more conscious about who is telling the stories, data they have chosen to highlight and what have they left out. Gives us some food for thought on how we assess ‘good’ research and researchers.